Large organizations often employ customer representatives to assist customers with a variety of matters, such as answering customer queries and resolving technical support issues. Today, customer representatives can interact with customers via a number of channels, for example live discussions over the phone or live chat dialogues over the internet. To ensure customer satisfaction and retention, it is important to provide customer representatives with sufficient tools to answer customer queries efficiently and effectively.
Typically, when an organization receives a phone call from a customer requesting assistance, a customer representative is provided with a static customer profile having some background information on the customer and context for the call. The customer profile may include information such as name, age, and a summary of any accounts held. A more advanced system may also include a summary of the last time the customer called, together with the previous customer representative's notes on the reason for the call. However, such systems do not take into account the multiple channels through which customers interact with organizations, and they are dependent on past customer representatives taking effective notes.
Additionally, current search tools to aid customer representatives in answering customer queries can be imprecise and cumbersome to use. For example, when a customer representative does not know the answer to a customer's question, the typical solution is to use a search engine that provides a list of pages of possible customer questions with links to stock answers. In this scenario, the customer representative needs to review the question and answer pages in detail to determine the best match to the customer's question and the answer to the question. This setup can result in increased wait time for the customer and increased difficulty for the customer representative. This setup may result not only in poor customer satisfaction but also higher early attrition of customer representatives.